# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
# Copyright 2021 Huawei Technologies Co., Ltd
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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/*
 * Copyright ©2019 Gaoang Wang.  All rights reserved.  Permission is
 * hereby granted for academic use.  No other use, copying, distribution, or modification
 * is permitted without prior written consent. Copyrights for
 * third-party components of this work must be honored.  Instructors
 * interested in reusing these course materials should contact the
 * author.
 */
  
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf
import numpy as np
import argparse
import facenet
import lfw
import os
import sys
import cv2
import pickle

from tensorflow.python.ops import data_flow_ops
from sklearn import metrics
from scipy.optimize import brentq
from scipy import interpolate
from scipy.interpolate import interp1d
from scipy.io import loadmat
from scipy import misc
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from sklearn import svm
from sklearn.externals import joblib
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification
from PIL import Image
import seq_nn_3d_v2
import tracklet_utils_3c
import track_lib



track_struct = tracklet_utils_3c.TC_tracker()

